Due to the large size of the data files required to produce a high quality representation of a digitally sampled image, it is common practice to apply various forms of compression to the data file in an attempt to reduce the size of the data file without adversely affecting the perceived image quality. Various well-known techniques and standards have evolved to address this need. Representative of these techniques is the Joint Photographic Experts Group (JPEG) standard for image encoding. Similar to JPEG, but with the addition of inter-frame encoding to take advantage of the similarity of consecutive frames in a motion sequence is the Moving Pictures Expert Group (MPEG) standard. Other standards and proprietary systems have been developed based on wavelet transforms.
In the process of a commercial movie DVD/HD-DVD release, a digital image that is scanned from conventional film, or from computer animated movie, typically has 10-bit data and, in certain applications, up to 16-bit data. The data is required to be converted to an 8-bit YUV format for compression. Due to the reduction of bit depth precision, banding artifacts often show up in the areas of the image, or images, with smooth color change. Dithering and error diffusion algorithms are commonly used to reduce the banding artifacts. In most dithering algorithms, a digital signal with high spatial frequency is added to the image to mask out the banding effect. However, the compression inside a DVD/HD-DVD is a lossy compression that removes signals with high spatial frequency. Therefore, the banding artifacts frequently show up after compression even if the banding is masked out by a dithering process before the compression.
The traditional approach for dithering or color depth reduction is for display applications and printing service. Since the dithering is the last step in the processing chain, added high spatial frequency is well preserved and serves the purpose of masking the banding effect when the color depth is reduced. Error diffusion is another common approach, where a quantization error is distributed around the neighboring pixels to generate masking effects and preserve overall image intensity. However, these approaches fail to consider the effect of a lossy compression, such as like MPEG1,2,4 or H.264, which tend to reduce or truncated the high frequency signal. Therefore, most of the error diffusion approaches will decrease the bit rate efficiency in the compression process, since a compression encoder will use a number of bits to represent the added quantization error and have fewer bits to represent the image. Meanwhile, the banding artifacts are prone to show up after the compression since the masking signal has been reduced or truncated.
Therefore, a need exists for techniques for reducing artifacts in images where the artifacts will remain reduced or suppressed after a lossy compression process. Furthermore, a need exists for techniques that will reduce artifacts in images while maintaining high bit rate efficiency.